Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Scientific Research Publishing

Cover, T. and Hart, P. (1967) Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13, 21-27.

ABSTRACT: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of ...
Visual Studio Magazine

Implementing k-Nearest Neighbors Regression Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...
GitHub

Prathu14hub/Task-6-K-Nearest-Neighbors-KNN-Classification

To understand and implement the K-Nearest Neighbors (KNN) algorithm for solving classification problems using the Iris dataset. This project demonstrates data preprocessing, model training, evaluation ...
Hosted on MSN

Why Nigeria Has As Many People As Its 15 Nearest Neighbors Combined Part 2

Scientists Found 7,000-Year-Old Mummies in the Desert That Don’t Share DNA With Modern Humans ‘Not My Signature’: Trump Fights Epstein Allegation Are you related to UK royal family? These last names ...
Scientific Research Publishing

Cover, T. and Hart, P. (1967) Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13, 21-27.

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...
IEEE

Dual Passive-Aggressive Stacking k-Nearest Neighbors for Class-Incremental Multi-Label Stream Classification

Abstract: Class-incremental multi-label stream classification (class-incremental MLSC) requires learning algorithms to adapt to concept drifts, perform single-pass online learning, and handle emerging ...
Frontiers

KDDC: a new framework that integrates kmers, dataset filtering, dimension reduction and classification algorithms to achieve immune cell heterogeneity classification

Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...